Improved species level bacterial characterization from rhizosphere soil of wilt infected Punica granatum

Pomegranate crops are prone to wilt complex disease, which is known to severely hamper the crop yield. There have been limited studies that have explored bacteria–plant–host associations in wilt complex disease affecting pomegranate crops. In the present study, wilt infected rhizosphere soil samples (ISI, ASI) in pomegranate were studied in comparison to a healthy control (HSC). The 16S metagenomics sequencing approach using the MinION platform was employed for screening of bacterial communities and predictive functional pathways. Altered physicochemical properties in the soil samples were recorded showing a comparatively acidic pH in the ISI (6.35) and ASI (6.63) soil samples to the HSC soil (7.66), along with higher electrical conductivity in the ISI (139.5 µS/cm), ASI soil (180 µS/cm), HSC soil sample (123.33 µS/cm). While concentration of micronutrients such as Cl and B were significantly higher in the ISI and ASI soil as compared to the HSC, Cu and Zn were significantly higher in the ASI soil. The effectiveness and accuracy of 16S metagenomics studies in identifying beneficial and pathogenic bacterial communities in multi-pathogen–host systems depend on the completeness and consistency of the available 16S rRNA sequence repositories. Enhancing these repositories could significantly improve the exploratory potential of such studies. Thus, multiple 16S rRNA data repositories (RDP, GTDB, EzBioCloud, SILVA, and GreenGenes) were benchmarked, and the findings indicated that SILVA yields the most reliable matches. Consequently, SILVA was chosen for further analysis at the species level. Relative abundance estimates of bacterial species showed variations of growth promoting bacteria, namely, Staphylococcus epidermidis, Bacillus subtilis, Bacillus megatarium, Pseudomonas aeruginosa, Pseudomonas putida, Pseudomonas stutzeri and Micrococcus luteus. Functional profiling predictions employing PICRUSt2 revealed a number of enriched pathways such as transporter protein families involved in signalling and cellular processes, iron complex transport system substrate binding protein, peptidoglycan biosynthesis II (staphylococci) and TCA cycle VII (acetate-producers). In line with past reports, results suggest that an acidic pH along with the bioavailability of micronutrients such as Fe and Mn could be facilitating the prevalence and virulence of Fusarium oxysporum, a known causative pathogen, against the host and beneficial bacterial communities. This study identifies bacterial communities taking into account the physicochemical and other abiotic soil parameters in wilt-affected pomegranate crops. The insights obtained could be instrumental in developing effective management strategies to enhance crop yield and mitigate the impact of wilt complex disease on pomegranate crops.


Materials and methods
Site description, sampling and physicochemical characterization. Rhizosphere soil samples were collected from an orchard close to Chikkaballapur region of Karnataka, India with coordinates of 13.3907° N, 77.6880° E. The farmer had experienced a streak of losses for five consecutive years at the time of this study, with no sign of abatement, and the losses appeared to be escalating. The soil samples were processed and the wilt infected samples were physically examined for disease symptoms confirming the presence of wilt like symptoms.
The plants were identified as wilt infected with Intermediate Stage Infection (ISI) and Advanced Stage Infection (ASI) on the basis of physical examination of the leaves, stem, fruits and roots. In the ISI sample, the fruits had dark coloured irregular spots with cracking, whereas in the severely infected plants the fruits were completely dry with dark brown pigmentation. Leaves showed yellowing, presence of moisture, dark-coloured irregular spots in the infected plants, and complete defoliation in the ASI or severely infected samples. The root systems of the infected plants were dry and reduced with elongated galls. Dark brown colouration of the stem which had turned completely dry was observed. Severely infected plants resulted in the production of infected fruits with no recovery. Soil samples of ISI and ASI were collected from four corners and one from the center of the orchard, each taken from plants showing similar symptoms. The samples were collected in triplicates, and then pooled. The samples were submitted under the BioProject name PRJNA540763 with the accession numbers infected sample ISI (SAMN11555162; SRR9002407) and severely infected sample ASI (SAMN11555163; SRR9002406). As a control HSC, sequence data of a healthy plant sample was used from a separate study (BioProject PRJNA540834; SRR9003394). The sample was collected from the same orchard under identical conditions 29 . Whole metagenome analysis of the samples ISI and ASI has been performed and published in a separate study and the presence of Fusarium oxysporum has been ascertained followed by further assessment of its adaptations 30 . All the necessary permissions to carry out this study have been obtained in accordance with the local state regulations. An overview of the entire protocol is depicted in Fig. 1 www.nature.com/scientificreports/ Physicochemical characterization and total microbial count estimation of the samples were carried out similar to the protocol outlined in our previous study employing whole metagenomics 30 . Sample preparation, microbial community DNA extraction and sequencing. DNA extraction and quality control. DNA from the soil samples was extracted using the commercially available DNeasy Powersoil kit (Catalog No. 12888-50) as per the manufacturer's recommendations. The soil sample was first prepared  ONT data analysis in QIIME2 framework. The FASTQ files were processed using the MetONTIIME pipeline (https:// github. com/ Maest Si/ MetON TIIME), a framework based on QIIME2 using Silva V138 (Silva 138 SSURef NR99) database and BLAST classifier. Parameters used were [-n 32 -c blast -m 10 -q 0.8 -i 0.8] 32 . The resulting BIOM file and obtained representative sequences were subjected to downstream functional analysis.
Functional profiling predictions and statistical analysis. PICRUSt2 was employed for predictive functional profiling analysis 33 and functional annotation of the sequences were based on Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology (KO; www. kegg. jp/ kegg/ kegg1. html). Pathways significance differentiation was further analyzed using statistical tests. All statistical tests including differential abundance analysis was performed using STAMP 2.1.3 (http:// kiwi. cs. dal. ca/ Softw are/ STAMP) for each of the samples. Two-sided Fisher's exact test was used to compare samples Storey's false discovery rate method of multiple test correction (p value ≤ 0.05) using DP at 95% confidence intervals 34 .
Ethical approval. All the necessary permissions to carry out this study have been obtained in accordance with the state regulations.

Results and discussion
The soil samples were collected from an orchard situated in Karnataka, India, which were categorized based on their stage of infection (ISI, ASI) and compared with a healthy sample (HSC). Physical examination of the plants, with respect to their roots, leaves, stem and fruits, revealed the presence of root knots in the wilt infected plants, which could be attributed to the root knot nematode, Meloidogyne. The soil from infected samples had a significantly lower pH compared to the healthy sample. The pH of ISI and ASI samples were 6.35 and 6.63, respectively, as compared to a pH of 7.66 in the healthy rhizosphere soil sample. Electrical conductivity (EC) was estimated to be 139.5 µS/cm in ISI soil, and significantly higher in the ASI soil (180 µS/cm) as compared to HSC soil sample (123.33 µS/cm). An estimated total N (0.191%), P (0.01%), K (0.01%), organic carbon (OC)(0.85%), Cl(18%), Fe (0.93%), Cu (26.33 ppm), Mn (9.10 ppm), Zn (30.9 ppm), B (4.1 ppm) were reported for the ISI soil. Cl and B were significantly higher in the ISI soil as compared to the HSC soil. On the other hand, for the ASI sample, the estimated total N (0.20%), P (0.11%), K (0.014%), OC (0.97%), Cl (21%), Fe (0.98%), Cu (31.4 ppm), Mn (9.6 ppm), Zn (33.2 ppm) and B (4.3 ppm) were reported. Cl, Cu, Zn and B were found to significantly higher in the ASI as compared to the HSC soil. No significant variations in the total bacterial and total fungal counts could be found within the samples. The HSC soil had a total bacterial and total fungal counts of 176 cfu/g and 2249.3 cfu/g, respectively. Whereas the corresponding total bacterial and total fungal counts for ISI and ASI soil were 2240 cfu/g and 170 cfu/g, and 2126 cfu/g and 154 cfu/g, respectively (Table 1).
In this study, the sequencing data generated from Nanopore sequencing platform was used for taxonomic profiling of microbial communities based on 16S rRNA sequencing. Sequence metrics of the samples from the MinION sequencing were estimated to be 36,000 sequence counts (ISI) and 31,868 (ASI) samples ( Table 2).
Comparison of databases. Accuracy in assigning bacterial lineages from Phylum to Genus level using classify-consensus-blast algorithm as furnished in Table 3.
At the phylum level, the GreenGenes database revealed the maximum number of hits 22 (Fig. 2).

pH EC (µs/cm) N (%) P (%) K (%) OC (%) Cl (%) Fe (%) Cu (ppm) Mn (ppm) Zn (ppm) B (ppm)
The highest number of correctly identified unique genera were returned from the SILVA database (n = 1681). Based on these results, the SILVA database was selected for further species level analysis of the samples.
Results show significant variations in the growth promoting bacterial species in the ISI soil sample as compared to the HSC soil. Bacillus species are known to produce several compounds such as antibiotics, siderophores, cell wall hydrolases and induced systemic resistance (ISR) that make them promising biocontrol agents 35,36 . Bacillus subtilis is a known biocontrol agent against wilt caused by C. fimbriata 37 . While significantly lower numbers of Bacillus subtilis were observed in the ISI soil, Bacillus megaterium was found to be significantly dominant in the On the other hand, an abundance of Micrococcus luteus has been reported in the ISI sample. Micrococcus luteus is a gram-positive bacterium that has been reported to exhibit antifungal activity 42,43 and its growth promoting properties, biocontrol properties 44 , biotic and abiotic stress tolerance 43 . Another study has reported the growth promoting properties of Micrococcus luteus against F.oxysporum in chickpea 45 . However, there are reports of Micrococcus luteus causing plant diseases. A study reported the role of Micrococcus luteus in leafspot disease in Mangifera indica 46 . More experimental evidence is required to validate the role of the Micrococcus luteus in the pathogenesis of the wilt disease in pomegranate.
Predictive pathway profiling. Pathway predictions performed using PICRUSt2 and subsequently with STAMP for statistical analysis of the results revealed a significant increase in the transporter protein families involved in signalling and cellular processes (Table 5).
K02015 (Iron complex transport system substrate binding protein), K02016 (Iron complex transport system substrate binding protein), K05846 osmoprotectant transport system permease protein, K03293 Amino acid www.nature.com/scientificreports/ transporter, K07024 sucrose-6-phosphatase and K02013 Iron-complex transport system showed significant increase in the ISI soil. The hits that showed significant increase in the ISI sample were K07498 putative transposases, K07497 putative transposase and K07052 uncharacterized protein (Fig. 4). It is noteworthy that iron complex transport system proteins are differentially abundant in the pathways predicted in the ISI soil sample. On the other hand, the most abundant pathways predicted in comparison to the ASI soil sample were transporter proteins involved in signalling and cellular processes, K07114 Ca-activated chlorine channel (CaCC), K02004 putative ABC transport system permease protein and K03088 RNA polymerase sigma-70 factor from ECF family (Fig. 4).
Peptidoglycan biosynthesis II (staphylococci) and TCA cycle VII (acetate-producers) were significantly enriched in ISI soil sample. In the ASI soil sample, aerobic respiration I (cytochrome c) and Kdo transfer to lipid IVA III (Chlamydia) pathways were found to be significantly enriched (Fig. 5).
Furthermore, correlating the findings, abiotic factors such as acidic pH, along with availability of iron (Fe) and manganese (Mn) have been reported to facilitate the growth of F. oxysporum, one that has a higher requirement for micronutrients 47 . The oxidation state of metals such as Fe and Mn determines their bioavailability, which is reportedly driven by the soil pH along with redox potential 48 .
The present study demonstrates the capabilities of the 16S rRNA sequencing platform in identifying potential key players involved in disease pathogenesis from soil samples collected from different pomegranate plants www.nature.com/scientificreports/ ranging from healthy to severely infected within the same orchard. Although various reports have described the disease symptoms in detail, the access to the diversity of the bacterial population can be facilitated through 16S rRNA sequencing using MinION. Examining the soil microbiome using 16S rRNA sequencing provides a platform for pathogenomics studies. These studies include exploring the microbial diversity and the key regulators that could provide valuable insights into the disease-causing pathogens, their adaptations and factors that influence their existence. A limitation to consider here is the amplicon-based prediction being less capable of strain-level identification. In a separate study, the microbiome of the infected soil samples the collection site have been explored extensively using the shotgun metagenomics approach 29 . This method offers improved sensitivity, resolution, and detailed characterization of microbial communities compared to traditional methods 49,50 . The study delved into the fungal communities and their adaptations, with a focus on Fusarium oxysporum, a known causative organism of wilt in pomegranate. The adaptations of this pathogen were also investigated. It is worth noting that wilt disease in pomegranate is caused by multiple pathogens and is often referred to as wilt complex. Furthermore, a number of beneficial bacterial communities Staphylococcus epidermidis, Bacillus subtilis, Bacillus megatarium, Micrococcus luteus, Pseudomonas aeruginosa were found in this study.
In particular, the present study revealed the prevalence or co-dominance of bacterial communities, which could be essential in establishing effective biocontrol strategies against wilt in pomegranate. Significant variations in the number of beneficial bacterial communities have been observed in this study. Current findings are consistent with our previous report on whole metagenome studies of infected samples 30 and other reports from literature. The results suggest that abiotic factors, such as an acidic pH and the availability of Fe and Mn, may be contributing to the growth of Fusarium oxysporum, as previously observed. Past reports have recommended that limiting bioavailable micronutrients such as Fe and Mn can serve as a biocontrol strategy. However, this finding has not been validated in the present study 47 . Nonetheless, a methodology is proposed for better characterization of bacterial species through 16S metagenome analysis. Furthermore, new knowledge and significant insights into the beneficial bacterial communities and enriched pathways have been revealed that may represent functional adaptations. As mentioned earlier, the accuracy and effectiveness of 16S metagenomics studies depends on the completeness and consistency of existing 16S rRNA sequence repositories. The information derived from such repositories plays a central role in identifying key players among both beneficial and pathogenic bacterial communities, which is demonstrated in the present study by exploring the complex multi-pathogen-host systems such as the Wilt complex.
In conclusion, this study reveals the complex interactions between bacteria, soil physicochemical properties, and the wilt complex disease affecting pomegranate crops. The proposed approach has the potential to improve the utilization of 16S metagenomics sequencing data for accurate microbial identification and functional profiling predictions. Overall, the study emphasises the significance of utilizing advanced approaches and technologies to precisely detect and characterize microbial communities in agricultural settings, taking into account abiotic factors such as soil physicochemical characteristics. Further investigation could result in substantial enhancements in the management and productivity of pomegranate crops.   G-test (W/Yate's) with Fischer's test and storey FDR multiple test correction has been implemented setting the significance threshold corrected-q value < 0.01 and a filter-difference between proportion with ES < 0.08.